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Failure Risk Prediction Using Artificial Neural Networks for Lightning Surge Protection of Underground MV Cables

机译:使用人工神经网络预测地下中压电缆的雷电浪涌的故障风险

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Lightning surge is actually being considered as one of the most dangerous events in power distribution systems. Basically, it hits the overhead distribution line then propagates to the other network components, such as underground cables and transformers. Due to lightning strokes, insulation failure of such components could occur. The failure risk can be determined on the basis of network configuration, its parameters, and surge arresters data. The determination of this index can greatly help in optimizing the network surge protection. The implementation of an artificial neural network (ANN) for prediction of the failure risk for underground medium-voltage cables connected to overhead distribution lines is introduced. The main advantage of ANN actually is the time and effort savings due to the random nature of the problem and extended calculation process. The calculation of the failure risk using ANN is applied to a group of industrial surge arresters. The results of the ANN test coincide with the analytical ones.
机译:雷电浪涌实际上被认为是配电系统中最危险的事件之一。基本上,它到达架空配电线路,然后传播到其他网络组件,例如地下电缆和变压器。由于雷击,可能会发生此类组件的绝缘故障。可以根据网络配置,其参数和电涌放电器数据确定故障风险。该指数的确定可以极大地帮助优化网络电涌保护。介绍了用于预测连接到架空配电线路的地下中压电缆的故障风险的人工神经网络(ANN)的实现。实际上,ANN的主要优点是由于问题的随机性和扩展的计算过程而节省了时间和精力。使用ANN进行故障风险的计算适用于一组工业电涌放电器。 ANN测试的结果与分析结果一致。

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